Adaptive Critic-Based Tracking Control of Non-Affine Nonlinear Discrete-time Systems with Unknown Dynamics

摘要：

In this paper, the tracking control of a class general non-affine discrete-time unknown systems represented by the nonlinear autoregressive moving average with eXogenous input (NARMAX) representation is discussed. An equivalent affine-like representation in terms of the tracking error dynamics is first obtained from the original nonaffine nonlinear discrete-time system so that a robust adaptive critic-based neural network controller can be developed. The control scheme consists of an action NN for compensating the unknown system dynamics, and a critic NN to approximate certain strategic utility function and to tune the action NN weights. The NN weights are tuned an online manner without the need of the knowledge of the system dynamics. By using the standard Lyapunov approach, the uniformly ultimate boundedness (UUB) of the closed-loop tracking error is shown. Simulation results are given substantiate the theoretical conclusions.

关键词： Non-affine nonlinear systems adaptive critic neural networks discrete-time

作者: Qinmin Yang Youxian Sun

作者单位: State Key Laboratory of Industrial Control Technology, Institute ofIndustrial Process Control, Zheji State Key Laboratory of Industrial Control Technology, Institute of Industrial Process Control, Zhej

会议类型: 国际会议

会议名称: 2011 China Control and Decision Conference(2011中国控制与决策会议 CCDC)

会议地点: 四川绵阳

会议语种:英文

页码: 2607-2612

在线出版日期: 2011-05-23（万方平台首次上网日期，不代表论文的发表时间）